This dataset provides the structured results of a systematic literature review on eco-efficiency in production processes. The included studies are analyzed and coded based on four analytical dimensions: (i) the conceptualization and application of eco-efficiency, (ii) methodological approaches, (iii) environmental and economic indicators, and (iv) system boundaries and levels of analysis. The dataset serves as the empirical basis for the analysis presented in the associated publication and enables transparency, reproducibility, and further use of the collected data. To systematically analyze the selected studies, a structured data extraction and coding approach is applied. Based on the theoretical foundations and research questions, a set of analytical dimensions is defined to capture how eco-efficiency is conceptualized and implemented in the context of production processes. These dimensions are operationalized in a structured evaluation matrix, in which each paper is assessed according to predefined criteria. The analysis focuses on four key aspects: (i) the conceptualization and application of eco-efficiency, distinguishing between explicit and implicit approaches as well as the level of operationalization; (ii) the methodological approaches used for environmental and economic assessment, differentiating between primary and secondary methods; (iii) the selection of environmental and economic indicators, which are grouped into higher-level categories to enable comparison across studies; and (iv) the system boundaries and levels of analysis, with particular attention to the consistency between environmental and economic perspectives. All studies are systematically coded according to these dimensions, allowing for a structured comparison and synthesis of the literature. This approach ensures a consistent evaluation across heterogeneous studies and enables the identification of patterns, commonalities, and methodological gaps in the application of eco-efficiency in production contexts.
Stefanowski et al. (Fri,) studied this question.